Curriculum Module
Created with R2020a. Compatible with R2020a and later releases.
This package contains a live script and supporting files to illustrate some basics of regression analysis. The materials are designed to be flexible and can be easily modified to accommodate a variety of teaching and learning methods. We include a brief background, interactive illustrations, tasks, reflection questions, a real-world application example, and a guided exercise for the concepts explored.
Learning Goals
- Define linear, nonlinear, and multiple linear regression.
- Assess and improve the performance of a regression model using a goodness-of-fit measure.
- Apply gradient descent to minimize a cost function.
- Explain the effect of increasing and decreasing the learning rate and number of steps for gradient descent.
- Apply a linear regression model to perform short-term forecasting.
MATLAB Onramp – a free two-hour introductory tutorial to learn the essentials of MATLAB®.
regressionBasics.mlx
An interactive lesson that introduces the fundamentals of regression analysis. Students apply basic linear regression to model real-world electricity load data.
electricityLoadData.mlx
A supplementary script to download the external electricity load data from New York ISO for use in the practice problem.
regressSolnIm/
This folder includes supplementary image files containing solutions for tasks in regressionBasics.mlx. The main script provides controls to hide or expose the solutions when needed. Ensure that this folder is in the same location as regressionBasics.mlx
MATLAB, Statistics and Machine Learning Toolbox™
The license for this module is available in the LICENSE.TXT file in this GitHub repository.
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